Featured Publications
Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions
Levey DF, Stein MB, Wendt FR, Pathak GA, Zhou H, Aslan M, Quaden R, Harrington KM, Nuñez YZ, Overstreet C, Radhakrishnan K, Sanacora G, McIntosh AM, Shi J, Shringarpure SS, Concato J, Polimanti R, Gelernter J. Bi-ancestral depression GWAS in the Million Veteran Program and meta-analysis in >1.2 million individuals highlight new therapeutic directions. Nature Neuroscience 2021, 24: 954-963. PMID: 34045744, PMCID: PMC8404304, DOI: 10.1038/s41593-021-00860-2.Peer-Reviewed Original ResearchConceptsTranscriptome-wide association studyMillion Veteran ProgramTranscriptome-wide association study (TWAS) analysisGenomic risk lociComplex psychiatric traitsGenetic architectureRisk lociGene expressionAssociation studiesLikely pathogenicityPsychiatric traitsVeteran ProgramNew therapeutic directionEuropean ancestryNew insightsAncestryUK BiobankAfrican ancestrySubstantial replicationExpressionLarge independent cohortsGWASTherapeutic directionsGenesLociGenome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits
Zhou H, Sealock JM, Sanchez-Roige S, Clarke TK, Levey DF, Cheng Z, Li B, Polimanti R, Kember RL, Smith RV, Thygesen JH, Morgan MY, Atkinson SR, Thursz MR, Nyegaard M, Mattheisen M, Børglum AD, Johnson EC, Justice AC, Palmer AA, McQuillin A, Davis LK, Edenberg HJ, Agrawal A, Kranzler HR, Gelernter J. Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. Nature Neuroscience 2020, 23: 809-818. PMID: 32451486, PMCID: PMC7485556, DOI: 10.1038/s41593-020-0643-5.Peer-Reviewed Original ResearchConceptsRegulatory genomic regionsGenome-wide association studiesNovel risk lociEuropean ancestry individualsPolygenic risk score analysisIndependent risk variantsGenetic architectureGenomic regionsRisk lociAssociation studiesGenetic relationshipsRisk genesGenetic correlationsPsychiatric traitsRisk variantsRisk score analysisTraitsGenetic heritabilityYields insightsBiobank samplesMendelian randomizationGenesLociBiologyHeritability
2023
Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses
Als T, Kurki M, Grove J, Voloudakis G, Therrien K, Tasanko E, Nielsen T, Naamanka J, Veerapen K, Levey D, Bendl J, Bybjerg-Grauholm J, Zeng B, Demontis D, Rosengren A, Athanasiadis G, Bækved-Hansen M, Qvist P, Bragi Walters G, Thorgeirsson T, Stefánsson H, Musliner K, Rajagopal V, Farajzadeh L, Thirstrup J, Vilhjálmsson B, McGrath J, Mattheisen M, Meier S, Agerbo E, Stefánsson K, Nordentoft M, Werge T, Hougaard D, Mortensen P, Stein M, Gelernter J, Hovatta I, Roussos P, Daly M, Mors O, Palotie A, Børglum A. Depression pathophysiology, risk prediction of recurrence and comorbid psychiatric disorders using genome-wide analyses. Nature Medicine 2023, 29: 1832-1844. PMID: 37464041, PMCID: PMC10839245, DOI: 10.1038/s41591-023-02352-1.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphism heritabilityGenome-wide analysisLikely causal genesFunctional genomics dataRisk variantsWide association studyPolygenic burdenPsychiatric disordersCausal genesPolygenic architectureGenomic dataRisk lociAssociation studiesSubgroups of depressionCause of disabilityDepression genetic riskCommon psychiatric disordersPrecision medicine approachCases of depressionOligodendrocyte lineageGenesLociConsiderable sex differencesGABAergic neuronsPsychiatric comorbidityMulti‐omics cannot replace sample size in genome‐wide association studies
Baranger D, Hatoum A, Polimanti R, Gelernter J, Edenberg H, Bogdan R, Agrawal A. Multi‐omics cannot replace sample size in genome‐wide association studies. Genes Brain & Behavior 2023, 22: e12846. PMID: 36977197, PMCID: PMC10733567, DOI: 10.1111/gbb.12846.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesLarge genome-wide association studiesNovel genesMulti-omics dataMulti-omics informationAssociation studiesGenome-wide significant lociSmall genome-wide association studyBrain-related traitsGWAS sample sizesEarly genome-wide association studiesNovel gene discoveryGene discoverySignificant lociAdditional genesPositional mappingHeritable traitVariant discoverySimilar traitsGenesNovel variant discoveryTraitsDisease biologyLociDiscoveryMultivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders
Hatoum A, Colbert S, Johnson E, Huggett S, Deak J, Pathak G, Jennings M, Paul S, Karcher N, Hansen I, Baranger D, Edwards A, Grotzinger A, Tucker-Drob E, Kranzler H, Davis L, Sanchez-Roige S, Polimanti R, Gelernter J, Edenberg H, Bogdan R, Agrawal A. Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders. Nature Mental Health 2023, 1: 210-223. PMID: 37250466, PMCID: PMC10217792, DOI: 10.1038/s44220-023-00034-y.Peer-Reviewed Original ResearchGenome-wide associationGenetic risk lociIndependent single nucleotide polymorphismsProblematic tobacco useSingle nucleotide polymorphismsRisk lociHigh polygenicityLociReceptor geneAddiction risk factorsPolygenic risk scoresEuropean descentPolygenicityGenesSummary statisticsSubstance use disordersSomatic conditionsAncestryRegulationConfersUse disordersPolymorphismGenetic liabilityDopamine regulationPDE4B
2022
Exploring the genetic overlap between twelve psychiatric disorders
Romero C, Werme J, Jansen P, Gelernter J, Stein M, Levey D, Polimanti R, de Leeuw C, Posthuma D, Nagel M, van der Sluis S. Exploring the genetic overlap between twelve psychiatric disorders. Nature Genetics 2022, 54: 1795-1802. PMID: 36471075, DOI: 10.1038/s41588-022-01245-2.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsPleiotropic single nucleotide polymorphismsPositive genetic correlationStringent P-value thresholdGenetic architectureGenomic regionsGenetic covarianceBiological processesBiological pathwaysMolecular characterizationObserved phenotypicGenetic correlationsGenetic overlapBiological characterizationBiological mechanismsP-value thresholdOnly annotationGenesPleiotropicPairwise comparisonsPhenotypicPathwayAnnotationPolymorphismCharacterizationGenome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways
Watanabe K, Jansen PR, Savage JE, Nandakumar P, Wang X, Hinds D, Gelernter J, Levey D, Polimanti R, Stein M, Van Someren E, Smit A, Posthuma D. Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways. Nature Genetics 2022, 54: 1125-1132. PMID: 35835914, DOI: 10.1038/s41588-022-01124-w.Peer-Reviewed Original ResearchConceptsRisk lociGenome-wide association studiesSpecific gene setsPrevious genome-wide association studyGene prioritization strategyExternal biological resourcesExtreme polygenicityExpression specificityAssociated lociSignaling functionsGene setsAssociation studiesNeuronal differentiationFunctional interactionGenesLociBiological resourcesPolygenicityNovel strategyPrioritization strategiesSpecific hypothesesDifferentiationPathwayStatistical powerLarge numberIntegrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder
Wingo TS, Gerasimov ES, Liu Y, Duong DM, Vattathil SM, Lori A, Gockley J, Breen MS, Maihofer AX, Nievergelt CM, Koenen KC, Levey DF, Gelernter J, Stein MB, Ressler KJ, Bennett DA, Levey AI, Seyfried NT, Wingo AP. Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder. Molecular Psychiatry 2022, 27: 3075-3084. PMID: 35449297, PMCID: PMC9233006, DOI: 10.1038/s41380-022-01544-4.Peer-Reviewed Original ResearchConceptsProteome-wide association studyTranscriptome-wide association studyGenome-wide association studiesBrain protein abundanceHuman brain proteomeBrain proteomeAssociation studiesProtein abundanceGenome-wide association dataHuman brain transcriptomePost-traumatic stress disorderGWAS resultsNovel proteinBrain transcriptomeRisk lociProteomeGenesAssociation dataPrecursor cellsPTSD pathogenesisBrain mRNA levelsMRNA levelsOligodendrocyte precursor cellsPromising targetNew insightsGenetically regulated multi-omics study for symptom clusters of posttraumatic stress disorder highlights pleiotropy with hematologic and cardio-metabolic traits
Pathak GA, Singh K, Wendt FR, Fleming TW, Overstreet C, Koller D, Tylee DS, De Angelis F, Cabrera Mendoza B, Levey DF, Koenen KC, Krystal JH, Pietrzak RH, O’ Donell C, Gaziano JM, Falcone G, Stein MB, Gelernter J, Pasaniuc B, Mancuso N, Davis LK, Polimanti R. Genetically regulated multi-omics study for symptom clusters of posttraumatic stress disorder highlights pleiotropy with hematologic and cardio-metabolic traits. Molecular Psychiatry 2022, 27: 1394-1404. PMID: 35241783, PMCID: PMC9210390, DOI: 10.1038/s41380-022-01488-9.Peer-Reviewed Original ResearchConceptsLocal genetic correlationsCell type-specific expressionVanderbilt University biorepositoryMulti-omics studiesMulti-omics investigationsDorsolateral prefrontal cortex tissueGenomic evidenceLaboratory traitsSpecific expressionCardio-metabolic traitsMillion Veteran ProgramPrefrontal cortex tissueMiR-148GenesGenetic correlationsRegulatory profileTraitsProtein expressionCardiometabolic traitsExpressionVeteran ProgramCortex tissueBiological heterogeneitySplicingPrioritization approach
2021
Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder
Johnson EC, Kapoor M, Hatoum AS, Zhou H, Polimanti R, Wendt FR, Walters RK, Lai D, Kember RL, Hartz S, Meyers JL, Peterson RE, Ripke S, Bigdeli TB, Fanous AH, Pato CN, Pato MT, Goate AM, Kranzler HR, O'Donovan MC, Walters JTR, Gelernter J, Edenberg HJ, Agrawal A. Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder. Psychological Medicine 2021, 53: 1196-1204. PMID: 34231451, PMCID: PMC8738774, DOI: 10.1017/s003329172100266x.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesGenome-wide significant single nucleotide polymorphismsLarge-scale genome-wide association studiesSignificant single nucleotide polymorphismsIndependent genome-wide significant single nucleotide polymorphismsSignificant genetic correlationsGenomic regionsSingle nucleotide polymorphismsGene expressionGenetic covariancePleiotropic associationsAssociation studiesGenetic correlationsGenetic variantsNucleotide polymorphismsGenetic overlapDisorder-specific effectsAlcohol use disorderGenetic influencesGenesUse disordersGenome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
Mullins N, Forstner AJ, O’Connell K, Coombes B, Coleman JRI, Qiao Z, Als TD, Bigdeli TB, Børte S, Bryois J, Charney AW, Drange OK, Gandal MJ, Hagenaars SP, Ikeda M, Kamitaki N, Kim M, Krebs K, Panagiotaropoulou G, Schilder BM, Sloofman LG, Steinberg S, Trubetskoy V, Winsvold BS, Won HH, Abramova L, Adorjan K, Agerbo E, Al Eissa M, Albani D, Alliey-Rodriguez N, Anjorin A, Antilla V, Antoniou A, Awasthi S, Baek JH, Bækvad-Hansen M, Bass N, Bauer M, Beins EC, Bergen SE, Birner A, Bøcker Pedersen C, Bøen E, Boks MP, Bosch R, Brum M, Brumpton BM, Brunkhorst-Kanaan N, Budde M, Bybjerg-Grauholm J, Byerley W, Cairns M, Casas M, Cervantes P, Clarke TK, Cruceanu C, Cuellar-Barboza A, Cunningham J, Curtis D, Czerski PM, Dale AM, Dalkner N, David FS, Degenhardt F, Djurovic S, Dobbyn AL, Douzenis A, Elvsåshagen T, Escott-Price V, Ferrier IN, Fiorentino A, Foroud TM, Forty L, Frank J, Frei O, Freimer NB, Frisén L, Gade K, Garnham J, Gelernter J, Giørtz Pedersen M, Gizer IR, Gordon SD, Gordon-Smith K, Greenwood TA, Grove J, Guzman-Parra J, Ha K, Haraldsson M, Hautzinger M, Heilbronner U, Hellgren D, Herms S, Hoffmann P, Holmans PA, Huckins L, Jamain S, Johnson JS, Kalman JL, Kamatani Y, Kennedy JL, Kittel-Schneider S, Knowles JA, Kogevinas M, Koromina M, Kranz TM, Kranzler HR, Kubo M, Kupka R, Kushner SA, Lavebratt C, Lawrence J, Leber M, Lee HJ, Lee PH, Levy SE, Lewis C, Liao C, Lucae S, Lundberg M, MacIntyre DJ, Magnusson SH, Maier W, Maihofer A, Malaspina D, Maratou E, Martinsson L, Mattheisen M, McCarroll SA, McGregor NW, McGuffin P, McKay JD, Medeiros H, Medland SE, Millischer V, Montgomery GW, Moran JL, Morris DW, Mühleisen TW, O’Brien N, O’Donovan C, Olde Loohuis LM, Oruc L, Papiol S, Pardiñas AF, Perry A, Pfennig A, Porichi E, Potash JB, Quested D, Raj T, Rapaport MH, DePaulo JR, Regeer EJ, Rice JP, Rivas F, Rivera M, Roth J, Roussos P, Ruderfer DM, Sánchez-Mora C, Schulte EC, Senner F, Sharp S, Shilling PD, Sigurdsson E, Sirignano L, Slaney C, Smeland OB, Smith DJ, Sobell JL, Søholm Hansen C, Soler Artigas M, Spijker AT, Stein DJ, Strauss JS, Świątkowska B, Terao C, Thorgeirsson TE, Toma C, Tooney P, Tsermpini EE, Vawter MP, Vedder H, Walters JTR, Witt SH, Xi S, Xu W, Yang JMK, Young AH, Young H, Zandi PP, Zhou H, Zillich L, Adolfsson R, Agartz I, Alda M, Alfredsson L, Babadjanova G, Backlund L, Baune B, Bellivier F, Bengesser S, Berrettini W, Blackwood D, Boehnke M, Børglum A, Breen G, Carr V, Catts S, Corvin A, Craddock N, Dannlowski U, Dikeos D, Esko T, Etain B, Ferentinos P, Frye M, Fullerton J, Gawlik M, Gershon E, Goes F, Green M, Grigoroiu-Serbanescu M, Hauser J, Henskens F, Hillert J, Hong K, Hougaard D, Hultman C, Hveem K, Iwata N, Jablensky A, Jones I, Jones L, Kahn R, Kelsoe J, Kirov G, Landén M, Leboyer M, Lewis C, Li Q, Lissowska J, Lochner C, Loughland C, Martin N, Mathews C, Mayoral F, McElroy S, McIntosh A, McMahon F, Melle I, Michie P, Milani L, Mitchell P, Morken G, Mors O, Mortensen P, Mowry B, Müller-Myhsok B, Myers R, Neale B, Nievergelt C, Nordentoft M, Nöthen M, O’Donovan M, Oedegaard K, Olsson T, Owen M, Paciga S, Pantelis C, Pato C, Pato M, Patrinos G, Perlis R, Posthuma D, Ramos-Quiroga J, Reif A, Reininghaus E, Ribasés M, Rietschel M, Ripke S, Rouleau G, Saito T, Schall U, Schalling M, Schofield P, Schulze T, Scott L, Scott R, Serretti A, Shannon Weickert C, Smoller J, Stefansson H, Stefansson K, Stordal E, Streit F, Sullivan P, Turecki G, Vaaler A, Vieta E, Vincent J, Waldman I, Weickert T, Werge T, Wray N, Zwart J, Biernacka J, Nurnberger J, Cichon S, Edenberg H, Stahl E, McQuillin A, Di Florio A, Ophoff R, Andreassen O. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nature Genetics 2021, 53: 817-829. PMID: 34002096, PMCID: PMC8192451, DOI: 10.1038/s41588-021-00857-4.Peer-Reviewed Original ResearchConceptsAssociation studiesQuantitative trait loci dataExpression quantitative trait loci (eQTL) dataGenome-wide association studiesBipolar disorder casesBrain-expressed genesWide association studyHeritable mental illnessSynaptic signaling pathwaysGenomic lociTargets of antipsychoticsLoci dataImperfect genetic correlationGene expressionSignaling pathwaysFunctional followGenesGenetic correlationsDruggable targetsSignal enrichmentEuropean ancestryLociBipolar disorder risk allelesNew insightsTherapeutic leadsPleiotropic effects of telomere length loci with brain morphology and brain tissue expression
Pathak GA, Wendt FR, Levey DF, Mecca AP, van Dyck CH, Gelernter J, Polimanti R. Pleiotropic effects of telomere length loci with brain morphology and brain tissue expression. Human Molecular Genetics 2021, 30: 1360-1370. PMID: 33831179, PMCID: PMC8255129, DOI: 10.1093/hmg/ddab102.Peer-Reviewed Original ResearchConceptsMethylation expressionGenetic variantsMapping gene functionTelomere lengthChromatin associationChromatin profilesGene functionGenetic colocalizationGene mappingGenomic relationshipsNeuropsychiatric traitsPleiotropic rolesDrug-gene interactionsCertain lociBrain tissue expressionGenesLociPleiotropic effectsBrain morphology measuresNucleotide polymorphismsAncestry populationsTissue expressionPhenotypic associationsPleiotropyAncestry groupsSex-stratified gene-by-environment genome-wide interaction study of trauma, posttraumatic-stress, and suicidality
Wendt FR, Pathak GA, Levey DF, Nuñez YZ, Overstreet C, Tyrrell C, Adhikari K, De Angelis F, Tylee DS, Goswami A, Krystal JH, Abdallah CG, Stein MB, Kranzler HR, Gelernter J, Polimanti R. Sex-stratified gene-by-environment genome-wide interaction study of trauma, posttraumatic-stress, and suicidality. Neurobiology Of Stress 2021, 14: 100309. PMID: 33665242, PMCID: PMC7905234, DOI: 10.1016/j.ynstr.2021.100309.Peer-Reviewed Original ResearchGenome-wide interaction studyRisk lociChromatin interaction profilesExtracellular matrix biologyGene-based analysisMatrix biologyMolecular basisTranscriptomic profilesInteraction studiesMultivariate geneGenetic perspectiveSNP effectsSuicidal behavior severityLociNovel targetGenesInteraction profilesSynaptic plasticityCellsInteractorsGenetic riskBiologyStressGxEIndependent cohort
2020
Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits
Quach BC, Bray MJ, Gaddis NC, Liu M, Palviainen T, Minica CC, Zellers S, Sherva R, Aliev F, Nothnagel M, Young KA, Marks JA, Young H, Carnes MU, Guo Y, Waldrop A, Sey NYA, Landi MT, McNeil DW, Drichel D, Farrer LA, Markunas CA, Vink JM, Hottenga JJ, Iacono WG, Kranzler HR, Saccone NL, Neale MC, Madden P, Rietschel M, Marazita ML, McGue M, Won H, Winterer G, Grucza R, Dick DM, Gelernter J, Caporaso NE, Baker TB, Boomsma DI, Kaprio J, Hokanson JE, Vrieze S, Bierut LJ, Johnson EO, Hancock DB. Expanding the genetic architecture of nicotine dependence and its shared genetics with multiple traits. Nature Communications 2020, 11: 5562. PMID: 33144568, PMCID: PMC7642344, DOI: 10.1038/s41467-020-19265-z.Peer-Reviewed Original ResearchConceptsGenome-wide significant lociGenome-wide association studiesNearby gene expressionExpression of genesSmoking traitsGenetic architectureSignificant lociGenetic variationMultiple traitsGene expressionAssociation studiesLociTraitsGenetic knowledgeComposite phenotypeUK BiobankExpressionTENM2GNAI1GenesGeneticsVariantsPhenotypeGenome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals
Xu K, Li B, McGinnis KA, Vickers-Smith R, Dao C, Sun N, Kember RL, Zhou H, Becker WC, Gelernter J, Kranzler HR, Zhao H, Justice AC. Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals. Nature Communications 2020, 11: 5302. PMID: 33082346, PMCID: PMC7598939, DOI: 10.1038/s41467-020-18489-3.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesLarge genome-wide association studiesMillion Veteran ProgramAssociation studiesExpression quantitative trait lociQuantitative trait lociChromatin interactionsComplex traitsFunctional annotationTrait lociSequencing ConsortiumDozen genesSignificant lociSmoking phenotypesLociMultiple populationsNew insightsPhenotypeVeteran ProgramGenetic vulnerabilityGenesTraitsAnnotationEuropean AmericansConsortium
2019
International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci
Nievergelt CM, Maihofer AX, Klengel T, Atkinson EG, Chen CY, Choi KW, Coleman JRI, Dalvie S, Duncan LE, Gelernter J, Levey DF, Logue MW, Polimanti R, Provost AC, Ratanatharathorn A, Stein MB, Torres K, Aiello AE, Almli LM, Amstadter AB, Andersen SB, Andreassen OA, Arbisi PA, Ashley-Koch AE, Austin SB, Avdibegovic E, Babić D, Bækvad-Hansen M, Baker DG, Beckham JC, Bierut LJ, Bisson JI, Boks MP, Bolger EA, Børglum AD, Bradley B, Brashear M, Breen G, Bryant RA, Bustamante AC, Bybjerg-Grauholm J, Calabrese JR, Caldas- de- Almeida J, Dale AM, Daly MJ, Daskalakis NP, Deckert J, Delahanty DL, Dennis MF, Disner SG, Domschke K, Dzubur-Kulenovic A, Erbes CR, Evans A, Farrer LA, Feeny NC, Flory JD, Forbes D, Franz CE, Galea S, Garrett ME, Gelaye B, Geuze E, Gillespie C, Uka AG, Gordon SD, Guffanti G, Hammamieh R, Harnal S, Hauser MA, Heath AC, Hemmings SMJ, Hougaard DM, Jakovljevic M, Jett M, Johnson EO, Jones I, Jovanovic T, Qin XJ, Junglen AG, Karstoft KI, Kaufman ML, Kessler RC, Khan A, Kimbrel NA, King AP, Koen N, Kranzler HR, Kremen WS, Lawford BR, Lebois LAM, Lewis CE, Linnstaedt SD, Lori A, Lugonja B, Luykx JJ, Lyons MJ, Maples-Keller J, Marmar C, Martin AR, Martin NG, Maurer D, Mavissakalian MR, McFarlane A, McGlinchey RE, McLaughlin KA, McLean SA, McLeay S, Mehta D, Milberg WP, Miller MW, Morey RA, Morris CP, Mors O, Mortensen PB, Neale BM, Nelson EC, Nordentoft M, Norman SB, O’Donnell M, Orcutt HK, Panizzon MS, Peters ES, Peterson AL, Peverill M, Pietrzak RH, Polusny MA, Rice JP, Ripke S, Risbrough VB, Roberts AL, Rothbaum AO, Rothbaum BO, Roy-Byrne P, Ruggiero K, Rung A, Rutten BPF, Saccone NL, Sanchez SE, Schijven D, Seedat S, Seligowski AV, Seng JS, Sheerin CM, Silove D, Smith AK, Smoller JW, Sponheim SR, Stein DJ, Stevens JS, Sumner JA, Teicher MH, Thompson WK, Trapido E, Uddin M, Ursano RJ, van den Heuvel LL, Van Hooff M, Vermetten E, Vinkers CH, Voisey J, Wang Y, Wang Z, Werge T, Williams MA, Williamson DE, Winternitz S, Wolf C, Wolf EJ, Wolff JD, Yehuda R, Young RM, Young KA, Zhao H, Zoellner LA, Liberzon I, Ressler KJ, Haas M, Koenen KC. International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci. Nature Communications 2019, 10: 4558. PMID: 31594949, PMCID: PMC6783435, DOI: 10.1038/s41467-019-12576-w.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesDisease genesAssociation studiesGenome-wide significant lociAfrican-ancestry analysesNon-coding RNAsGenetic risk lociParkinson's disease genesEuropean ancestry populationsNovel genesSignificant lociGenetic variationSpecific lociRisk lociAdditional lociLociAncestry populationsCommon variantsHeritability estimatesGenesGWASRNABiologySNPsPARK2Epigenome‐Wide DNA Methylation Association Analysis Identified Novel Loci in Peripheral Cells for Alcohol Consumption Among European American Male Veterans
Xu K, Montalvo‐Ortiz J, Zhang X, Southwick SM, Krystal JH, Pietrzak RH, Gelernter J. Epigenome‐Wide DNA Methylation Association Analysis Identified Novel Loci in Peripheral Cells for Alcohol Consumption Among European American Male Veterans. Alcohol Clinical And Experimental Research 2019, 43: 2111-2121. PMID: 31386212, PMCID: PMC9377208, DOI: 10.1111/acer.14168.Peer-Reviewed Original ResearchConceptsEpigenome-wide association studiesDNA methylationCpG sitesSignificant CpG sitesHigh-density methylation arraysNovel DNA methylation sitesNew CpG sitesDNA methylation sitesEpigenome-wide DNA methylationAmino acid transportIndividual CpG sitesGene lengthPeripheral cellsNovel lociDNA sitesKEGG databaseMethylation sitesEnrichment analysisMethylation arraysAssociation studiesAssociation analysisGenesMethylationAcid transportFalse discovery rateGenome‐wide scan identifies opioid overdose risk locus close to MCOLN1
Cheng Z, Yang B, Zhou H, Nunez Y, Kranzler HR, Gelernter J. Genome‐wide scan identifies opioid overdose risk locus close to MCOLN1. Addiction Biology 2019, 25: e12811. PMID: 31362332, PMCID: PMC7485539, DOI: 10.1111/adb.12811.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesMucolipin-1Expression profilesGenome-wide significant signalsAssociation studiesPost-GWAS analysisWide association studyDrug repositioning analysisCation channel activityFunctional categoriesConnectivity Map databaseDrug targetsRisk genesGenesChannel activityPatatin-like phospholipaseNetwork analysisPNPLA6Significant signalEuropean AmericansGenomewide Study of Epigenetic Biomarkers of Opioid Dependence in European- American Women
Montalvo-Ortiz JL, Cheng Z, Kranzler HR, Zhang H, Gelernter J. Genomewide Study of Epigenetic Biomarkers of Opioid Dependence in European- American Women. Scientific Reports 2019, 9: 4660. PMID: 30874594, PMCID: PMC6420601, DOI: 10.1038/s41598-019-41110-7.Peer-Reviewed Original ResearchConceptsEpigenome-wide association studiesEpigenetic mechanismsAssociation studiesAssociation analysisCpG sitesFirst epigenome-wide association studyGenome-wide association studiesPrevious genome-wide association studyCandidate gene approachChromatin remodelingDNA bindingGene approachGenomewide studiesDNA methylation ageCell survivalEpigenetic biomarkersRisk variantsPopulation stratificationMethylation ageGenesCell projectionsOpioid dependenceNovel peripheral biomarkersEuropean American womenCell proportionAlcohol-responsive genes identified in human iPSC-derived neural cultures
Jensen KP, Lieberman R, Kranzler HR, Gelernter J, Clinton K, Covault J. Alcohol-responsive genes identified in human iPSC-derived neural cultures. Translational Psychiatry 2019, 9: 96. PMID: 30862775, PMCID: PMC6414668, DOI: 10.1038/s41398-019-0426-5.Peer-Reviewed Original ResearchConceptsAlcohol-responsive genesGene expressionGene regulatory effectsTotal RNA sequencingCo-expressed genesNeural cell culturesCholesterol biosynthesis pathwayPrimary neural tissueCorrelation network analysisHuman-induced pluripotent stem cellsPluripotent stem cellsBiosynthesis pathwayCell culturesResponsive genesRNA sequencingNotch signalingEnrichment analysisMolecular mechanismsCell cycleAlcohol exposureGenesCell culture modelGenetic effectsCholesterol homeostasisStem cells